CN113608178B - Anti-drag deception jamming method based on dual-band information fusion - Google Patents
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
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- G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
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Abstract
The invention discloses a method for resisting dragging deception interference based on dual-band information fusion, which comprises the steps of firstly, respectively utilizing measurement information of two bands to perform angle clustering treatment, realizing the angle clustering of dense interference measurement in a specific direction, performing distance speed association analysis through historical measurement in the angle clustering, preliminarily realizing the discrimination of interference and targets, eliminating suspected interference measurement and improving the recognition speed of interference; finally, the real target is judged by performing distance-speed-angle matching on the temporary tracks of the two wave bands, so that the target identification probability can be improved, and the anti-interference capability of the system is enhanced.
Description
Technical Field
The invention relates to the technical field of radar anti-interference, in particular to a method for resisting drag deception interference based on dual-band information fusion.
Background
With the improvement of digital technology and signal processing capability, the technology of deceptive jamming has been rapidly developed. The deceptive interference has strong correlation with the target, high interference resistance difficulty and serious threat to the radar, so that the traditional radar interference resistance method is more and more difficult to meet the combat requirement in the complex electromagnetic environment, and the exertion of the radar on the target detection and tracking performance is seriously influenced.
The premise of resisting the active deception jamming signals is that the radar can correctly identify the jamming signals, the existing method can identify the active deception jamming signals in radar receiving wave gates of frequency domain, time-frequency domain, high-order spectral domain or polarization domain, and a learner can identify the target signals and the jamming signals in the radar receiving wave gates by extracting amplitude statistics characteristic difference methods between the target signals and the jamming signals, but the method is sensitive to noise and has good target signal or jamming signal identification rate under the condition of high signal-to-noise ratio. Secondly, the model established by the method is too ideal, so that the method can be disabled when a target signal and an interference signal exist in a radar receiving wave gate at the same time.
The basic principle of radar anti-interference is mainly to make use of the difference of the multi-dimensional modulation characteristics of the interference signal and the real target echo signal in the time domain, the frequency domain, the space domain, the polarization domain and the like, so that the radar signal and the data processing system can be matched with the modulation characteristics of the real target echo to the maximum extent, the influence of various interferences is inhibited to the maximum extent, and the highest signal-to-noise ratio are obtained during target detection and parameter measurement. However, when the target and the drag spoof bait are both indistinguishable in the space-time-frequency domain, the conventional single-segment seeker does not have the capability of resisting drag spoof interference. It is therefore desirable to introduce dual bands for fusion anti-fraud.
The patent 'distance-speed synchronous towing spoofing interference identification based on gradient projection' (publication number: CN 103837863A) describes a method for calculating the Doppler speed of a target against distance-speed synchronous towing by using a gradient projection method. The method can synchronously drag the deception target at the distance-speed, but the target which is indistinguishable to time-frequency has the risk of not identifying the target with low resolution. The method provided by the patent can realize clustering on angles, and can identify interference by utilizing angle clustering information of two wave bands, and can still perform interference identification under the condition of a time-frequency indistinguishable target.
The patent 'a method for resisting speed deception jamming of an airborne pulse Doppler radar' (publication number: CN 104678367A) introduces a method for resisting speed deception jamming of a radar single target, wherein targets are detected and tracked by using the radar, the tracking center frequency of the single target point is obtained, and the frequency weights of a plurality of targets are calculated by using a weighting coefficient method and sent to a radar tracking center so as to realize speed deception jamming judgment. However, the method is simple aiming at the interference type and cannot effectively resist angle spoofing interference.
The patent 'self-adaptive iterative filtering method for resisting distance-speed combined spoofing interference of radar' (publication number: CN 105954729A) introduces a self-adaptive iterative filtering method for resisting distance-speed combined spoofing interference of radar, which respectively estimates the distance and pulse dimensions of a target and interference, and then improves the accuracy of an algorithm through iteration. But this method must know the number of pulses interfering with the relative target delay, and in practice, this condition is often difficult to meet and engineering practicality is relatively poor.
The patent 'a radar interference recognition method with synchronous towing of distance and speed' (publication number: CN 105866749A) introduces a broadband radar interference recognition method with synchronous towing of distance and speed, and the recognition of targets and interference is carried out by extracting effective and steady interference signal error angles by utilizing the spectrum characteristic difference of interference signals and target signals. Although the method is small in calculated amount and easy to implement, the method has a large influence on the interference error angle by the phase quantization bit number of the jammer, and the situation of interference identification failure is easy to occur.
The paper name is "single pulse angle tracking radar towed interference angle separation method" (electronic information countermeasure technology, 2019, 34 (2): 37-40) which indicates that a spatial spectrum estimation technology is utilized to propose an equidistant multi-target super-resolution method based on a beam domain, so that the separation of towed decoys and target angle dimensions is realized. However, when the signal-to-noise ratio is low, the towed interference and the target angle error cannot be separated, and the self-adaptive angle clustering threshold provided by the patent can be adjusted according to the signal-to-noise ratio, so that the recognition probability of the towed interference and the target is improved.
The paper name is "method research of anti-drag interference of terminal guidance radar" (guidance and fuze, 2019.9, 40 (3): 1-5) proposes a method for suppressing interference by utilizing polarization filtering based on polarization characteristic difference of target and interference, and realizing monopulse angle measurement. However, in practice, the target polarization scattering characteristics are not known, and after the polarization interference suppression, a certain loss of signal-to-noise ratio occurs, which affects the angular performance.
The method can not achieve the expected effect of effectively identifying the real target under the condition that the target and the deception jamming can not be identified in the space-time-frequency domain, and the method is an anti-jamming method aiming at the time-frequency dimension or the angle dimension, and has no general anti-jamming method and can simultaneously resist the deception jamming in the space-time-frequency domain.
Disclosure of Invention
The invention aims to provide a method for resisting drag deception jamming by means of dual-band information fusion, which comprises the steps of firstly carrying out rapid identification of targets and jamming by means of angle clustering results of two bands, accurately identifying deception jamming by means of distance speed fusion information of the two bands, improving identification probability of the targets and enhancing anti-jamming capability of a system.
In order to achieve the above purpose, the present invention is realized by the following technical scheme:
the anti-drag deception jamming method based on the dual-band information fusion is characterized by comprising the following steps of:
s1, respectively aiming at two different wave bands, determining an adaptive threshold of angle clustering according to the angle and signal-to-noise ratio information of statistical measurement;
s2, angle clustering is carried out on the measurement of different wave bands according to the self-adaptive threshold, azimuth angle difference and pitching angle difference between every two measurements are calculated, and when the azimuth angle difference and pitching value of the two measurements are smaller than the corresponding angle clustering threshold G 1 +G 2 When it is determined that the two measurements belong to the same cluster, wherein G 1 ，G 2 The self-adaptive angle clustering thresholds of measurement 1 and measurement 2 are respectively;
s3, realizing clustering and group association, and constructing a group on the basis of clustering, wherein the group comprises historical measurement information of an angle clustering center; calculating the angle difference between the clustering angle center and the group angle center, and extracting the angle clustering difference of the target and the interference to preliminarily realize the judgment of the interference and the target when the angle difference is smaller than the corresponding association threshold;
s4, aiming at a single wave band, firstly, respectively processing information of each group by utilizing a speed and distance towing recognition algorithm, primarily recognizing distance and speed deception interference measurement, removing suspected deception measurement, and performing multi-target tracking processing by utilizing the rest group information to form a plurality of groups of temporary tracks;
s5, performing distance-speed-angle matching processing on the temporary tracks of the two wave bands, accurately identifying the target track, and further eliminating drag deception interference, so that drag deception processing is realized.
Optionally, in the step S1, the adaptive threshold of the angle clustering is proportional to the signal-to-noise ratio SNR and is 3dB beamwidth θ of the radar guide 3dB Inversely proportional, the scaling factor is ζ, thus the adaptive threshold can be determined as
Optionally, the step S2 specifically includes:
s21, traversing all the measurements of the current frame, calculating azimuth angle errors and pitch angle errors among the measurements, and setting corresponding elements of a measurement cluster chain table matrix mu [ m multiplied by m ] to be 1 when the two angle differences are smaller than a threshold, wherein m is the measurement number; for each measurement, the used flag is cleared to 0; traversing all the measurements, and creating a cluster when the measurements are not used; when a cluster is newly established, initializing the cluster;
s22, traversing all the measurements, and adding the measurement into the new cluster when the element of the linked list matrix mu [ m multiplied by m ] corresponding to all the measurement in the cluster is 1 and the measurement is not used; the method comprises the steps of circulating in this way until all the measurement traversal is completed, inserting the newly built clusters into a cluster linked list, and activating the clusters;
s23, after the clustering is finished, the number of the clusters is the number of the measurement corresponding to the current frame time targets, namely, the number of the targets from which the current frame time measurement is performed can be calculated.
Optionally, the step S3 specifically includes:
s31, calculating the azimuth angle difference of the clusters and the groups asCalculating the pitch angle difference of the clusters and the groups to be +.>Calculating the maximum value of the two as +.>
S32, traversing all clusters for the existing group, selecting the cluster with the smallest delta, and if the cluster corresponds to the existing groupAnd->Determining that the group is associated with the cluster if the extrapolation time of the group is less than the threshold value; if a plurality of groups are associated with each cluster at the same time, selecting and rejecting according to a nearest neighbor method;
s33, the rapid interference recognition can be realized only when the angle clustering results of the two wave bands are different, and the radar jammer is not easy to realize the interference of the two wave bands at the same time, so that the clustering can be rapidly recognized as the interference according to the clustering of one wave band and the clustering of the other wave band aiming at the angle clustering result of the two wave bands.
Optionally, in the step S4, if the interference is not identified by using the angle clustering in the step S3, a secondary decision is required to be made through the speed distance measurement statistical information, so as to finally realize the identification of the target and the interference:
s41, aiming at speed dragging deception jamming, defining the distance measured by current frame clustering as R in sequence 1 ,R 2 ,…,R n The corresponding speeds are v in turn 1 ,v 2 ,…,v n The speed obtained by the previous frame of deblurring is v, and the time interval is T s ，||e ij ||＝R i -R j ；
S42, traversing the measurement distance R 1 To R n When e ij When the I is less than or equal to xi (the xi is a small number), the i row and the j column L of the distance equality matrix ij ＝L ji =1, otherwise L ij ＝L ji ＝0；
S43, traversing the matrix L, wherein the matrix L is traversed,
s44, traversing the measurement, wherein the step of measuring,
V re,i (k)＝||v ij ||,if||v ij ||＞0(j＝1,...,m,j≠i,k＝k+1)
V min ＝min(V re,i (k)) (k≥2)
drag counter C when measuring the speed of i re,i When the speed is more than or equal to 2, speed dragging interference exists and a corresponding measured dragging mark is set to be true;
s45, suppressing the towing interference measurement;
a i ＝||v i V|/Ts (measurement i is a velocity trailing measurement)
When a is i ＞η a When the measurement i is set to be unreliable, where η a Is an acceleration threshold.
Optionally, in the step S5, the distance-speed-angle recognition results of the two wave bands are fused to accurately recognize the target and the interference, thereby realizing anti-drag spoofing interference; and if the modulus values of the speed difference and the distance difference memory angle difference in the corresponding tracks formed by the two wave bands are smaller than the corresponding threshold, the corresponding track is regarded as a target, and otherwise, the corresponding track is deception jamming.
Compared with the prior art, the invention has the following advantages:
1) The invention adopts the self-adaptive clustering threshold, and can adjust the angle clustering threshold of the target and the interference according to the signal-to-noise ratio, thereby more accurately distinguishing the target from the interference.
2) The invention uses angle clustering process, can classify the interference and the target from space, overcomes the defect that the interference and the target characteristics can only be obtained from the distance and speed dimension information in the prior art, adds the other dimension information for identifying the interference and the target, and can more reliably distinguish the target from the interference;
3) The invention utilizes the angle clustering information of the double wave bands to quickly and preliminarily realize the judgment of the interference and the target, thereby improving the interference recognition speed, increasing the recognition probability of the target and enhancing the anti-interference capability of the system.
4) According to the invention, the speed distance angle difference of the tracks of the two wave bands is compared by establishing the tracks of the two wave bands, so that the target and the interference are accurately identified, and the anti-drag deception interference is realized.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed for the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic view of clustering angle measurements in an embodiment of the present invention;
fig. 2 is a flowchart of a method for anti-drag spoofing based on dual-band information fusion in an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. It should be noted that the drawings are in a very simplified form and are all to a non-precise scale, merely for the purpose of facilitating and clearly aiding in the description of embodiments of the invention. For a better understanding of the invention with objects, features and advantages, refer to the drawings. It should be understood that the structures, proportions, sizes, etc. shown in the drawings are for illustration purposes only and should not be construed as limiting the invention to the extent that any modifications, changes in the proportions, or adjustments of the sizes of structures, proportions, or otherwise, used in the practice of the invention, are included in the spirit and scope of the invention which is otherwise, without departing from the spirit or essential characteristics thereof.
It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.
Referring to fig. 1 and 2, the present embodiment provides a method for anti-drag spoofing interference based on dual-band information fusion, which includes the following steps:
s1, angle measurement analysis is carried out on two wave bands according to the two different wave bands respectively, and signal to noise ratio information is counted to determine an adaptive threshold of angle clustering, wherein the threshold of the angle clustering is related to the signal to noise ratio and the wave beam width;
s2, angle clustering is carried out on the measurement of different wave bands according to the self-adaptive threshold, azimuth angle difference and pitching angle difference between every two measurements are calculated, and when the azimuth angle difference and pitching value of the two measurements are smaller than the corresponding angle clustering threshold G 1 +G 2 When it is determined that two measurements belong to the same cluster, whichIn (G) 1 ，G 2 The self-adaptive angle clustering thresholds of measurement 1 and measurement 2 are respectively;
s3, realizing clustering and group association, and constructing a group on the basis of clustering, wherein the group comprises historical measurement information of an angle clustering center; calculating the angle difference between the clustering angle center and the group angle center, and extracting the angle clustering difference of the target and the interference to preliminarily realize the judgment of the interference and the target when the angle difference is smaller than the corresponding association threshold;
s4, aiming at a single wave band, firstly, respectively processing information of each group by utilizing a speed and distance towing recognition algorithm, primarily recognizing distance and speed deception interference measurement, removing suspected deception measurement, and performing multi-target tracking processing by utilizing the rest group information to form a plurality of groups of temporary tracks;
s5, performing distance-speed-angle matching processing on the temporary tracks of the two wave bands, accurately identifying the target track, and further eliminating drag deception interference, so that drag deception processing is realized.
In this embodiment, in the step S1, the adaptive threshold of the angle clustering is proportional to the SNR and 3dB beamwidth θ of the radar guide head 3dB Inversely proportional, the scaling factor is ζ, thus the adaptive threshold can be determined as
In this embodiment, the step S2 specifically includes:
s21, traversing all the measurements of the current frame, calculating azimuth angle errors and pitch angle errors among the measurements, and setting corresponding elements of a measurement cluster chain table matrix mu [ m multiplied by m ] to be 1 when the two angle differences are smaller than a threshold, wherein m is the measurement number; for each measurement, the used flag is cleared to 0; traversing all the measurements, and creating a cluster when the measurements are not used; when a cluster is newly built, initializing the cluster (the cluster creation mark is set to be 1, the measurement number is set to be 1, and the measurement sequence number is recorded);
s22, traversing all the measurements, and adding the measurement into the new cluster when the element of the linked list matrix mu [ m multiplied by m ] corresponding to all the measurement in the cluster is 1 and the measurement is not used; the method comprises the steps of circulating in this way until all the measurement traversal is completed, inserting the newly built clusters into a cluster linked list, and activating the clusters;
s23, after the clustering is finished, the number of the clusters is the number of the measurement corresponding to the current frame time targets, namely, the number of the targets from which the current frame time measurement is performed can be calculated.
In this embodiment, the step S3 specifically includes:
s31, calculating the azimuth angle difference of the clusters and the groups asCalculating the pitch angle difference of the clusters and the groups to be +.>Calculating the maximum value of the two as +.>
S32, traversing all clusters for the existing group, selecting the cluster with the smallest delta, and if the cluster corresponds to the existing groupAnd->Determining that the group is associated with the cluster if the extrapolation time of the group is less than the threshold value; if a plurality of groups are associated with each cluster at the same time, selecting and rejecting according to a nearest neighbor method;
s33, the rapid interference recognition can be realized only when the angle clustering results of the two wave bands are different, and the radar jammer is not easy to realize the interference of the two wave bands at the same time, so that the clustering can be rapidly recognized as the interference according to the clustering of one wave band and the clustering of the other wave band aiming at the angle clustering result of the two wave bands.
In this embodiment, in the step S4, if the interference cannot be identified by using the angle clustering in the step S3, a secondary decision is required to be made through the speed distance measurement statistical information, so as to finally realize the identification of the target and the interference:
s41, aiming at speed dragging deception jamming, defining the distance measured by current frame clustering as R in sequence 1 ,R 2 ,…,R n The corresponding speeds are v in turn 1 ,v 2 ,…,v n The speed obtained by the previous frame of deblurring is v, and the time interval is T s ，||e ij ||＝R i -R j ；
S42, traversing the measurement distance R 1 To R n When e ij When the I is less than or equal to xi (the xi is a small number), the i row and the j column L of the distance equality matrix ij ＝L ji =1, otherwise L ij ＝L ji ＝0；
S43, traversing the matrix L, wherein the matrix L is traversed,
s44, traversing the measurement, wherein the step of measuring,
V re,i (k)＝||v ij ||,if||v ij ||＞0(j＝1,...,m,j≠i,k＝k+1)
V min ＝min(V re,i (k)) (k≥2)
drag counter C when measuring the speed of i re,i When the speed is more than or equal to 2, speed dragging interference exists and a corresponding measured dragging mark is set to be true;
s45, suppressing the towing interference measurement;
a i ＝||v i V|/Ts (measurement i is a velocity trailing measurement)
When a is i ＞η a When the measurement i is set to be unreliable, where η a Is an acceleration threshold;
s46, the distance towing interference recognition algorithm is similar to the speed towing interference recognition algorithm in thought, and the description is omitted.
In this embodiment, in the step S5, the distance-speed-angle recognition results of the two wave bands are fused to accurately recognize the target and the interference, thereby realizing anti-drag spoofing interference; and if the modulus values of the speed difference and the distance difference memory angle difference in the corresponding tracks formed by the two wave bands are smaller than the corresponding threshold, the corresponding track is regarded as a target, and otherwise, the corresponding track is deception jamming.
While the present invention has been described in detail through the foregoing description of the preferred embodiment, it should be understood that the foregoing description is not to be considered as limiting the invention. Many modifications and substitutions of the present invention will become apparent to those of ordinary skill in the art upon reading the foregoing. Accordingly, the scope of the invention should be limited only by the attached claims.
Claims (6)
1. The anti-drag deception jamming method based on the dual-band information fusion is characterized by comprising the following steps of:
s1, respectively aiming at two different wave bands, determining an adaptive threshold of angle clustering according to the angle and signal-to-noise ratio information of statistical measurement;
s2, angle clustering is carried out on the measurement of different wave bands according to the self-adaptive threshold of the angle clustering, azimuth angle difference and pitching angle difference between every two measurements are calculated, and when the azimuth angle difference and pitching angle difference of the two measurements are smaller than the self-adaptive threshold G of the corresponding angle clustering 1 +G 2 When it is determined that the two measurements belong to the same cluster, wherein G 1 ，G 2 The self-adaptive threshold of the angle clustering of the measurement 1 and the measurement 2 is respectively;
s3, realizing clustering and group association, and constructing a group on the basis of clustering, wherein the group comprises historical measurement information of an angle clustering center; calculating the angle difference between the clustering angle center and the group angle center, and extracting the angle clustering difference of the target and the interference to preliminarily realize the judgment of the interference and the target when the angle difference is smaller than the corresponding association threshold;
s4, aiming at a single wave band, firstly, respectively processing information of each group by utilizing a speed and distance towing recognition algorithm, primarily recognizing distance and speed deception interference measurement, removing suspected deception measurement, and performing multi-target tracking processing by utilizing the rest group information to form a plurality of groups of temporary tracks;
s5, performing distance-speed-angle matching processing on the temporary tracks of the two wave bands, accurately identifying the target track, and further eliminating drag deception interference, so that drag deception processing is realized.
2. The method of anti-drag-and-fraud based on dual-band information fusion as defined in claim 1, wherein in the step S1, the adaptive threshold of the angular clustering is proportional to the signal-to-noise ratio SNR and is 3dB beamwidth θ of the radar seeker 3dB In inverse proportion, the scaling factor is ζ, so that the adaptive threshold of the angle cluster can be determined as
3. The method of anti-drag spoofing interference based on dual band information fusion of claim 1, wherein the step S2 specifically comprises:
s21, traversing all the measurements of the current frame, calculating azimuth angle errors and pitch angle errors among the measurements, and setting corresponding elements of a measurement cluster linked list matrix mu [ m multiplied by m ] to be 1 when the two angle differences are smaller than the self-adaptive threshold of angle clustering, wherein m is the measurement number; for each measurement, the used flag is cleared to 0; traversing all the measurements, and creating a cluster when the measurements are not used; when a cluster is newly established, initializing the cluster;
s22, traversing all the measurements, and adding the measurement into the new cluster when the element of the linked list matrix mu [ m multiplied by m ] corresponding to all the measurement in the cluster is 1 and the measurement is not used; the method comprises the steps of circulating in this way until all the measurement traversal is completed, inserting the newly built clusters into a cluster linked list, and activating the clusters;
s23, after the clustering is finished, the number of the clusters is the number of the measurement corresponding to the current frame time targets, namely, the number of the targets from which the current frame time measurement is performed can be calculated.
4. The method for anti-drag and fraud interference based on dual-band information fusion as defined in claim 3, wherein the step S3 specifically comprises:
s31, calculating the azimuth angle difference of the clusters and the groups asCalculating the pitch angle difference of the clusters and the groups asCalculating the maximum value of the two as +.>
S32, traversing all clusters for the existing group, selecting the cluster with the smallest delta, and if the cluster corresponds to the existing groupAnd->Determining that the group is associated with the cluster if the extrapolation time of the group is smaller than the corresponding association threshold and the extrapolation time of the group is smaller than the threshold; if a plurality of groups are associated with each cluster at the same time, selecting and rejecting according to a nearest neighbor method;
s33, the rapid interference recognition can be realized only when the angle clustering results of the two wave bands are different, and the radar jammer is not easy to realize the interference of the two wave bands at the same time, so that the clustering can be rapidly recognized as the interference according to the clustering of one wave band and the clustering of the other wave band aiming at the angle clustering result of the two wave bands.
5. The anti-drag spoofing interference method based on dual band information fusion as defined in claim 4, wherein in the step S4, if no interference is identified by using the angle clustering in the step S3, a secondary decision is required by the speed distance measurement statistical information, and finally the identification of the target and the interference is realized:
s41, aiming at speed dragging deception jamming, defining the distance measured by current frame clustering as R in sequence 1 ,R 2 ,…,R n The corresponding speeds are v in turn 1 ,v 2 ,…,v n The speed obtained by the previous frame of deblurring is v, and the time interval is T s ，||e ij ||＝R i -R j ；
S42, traversing the measurement distance R 1 To R n When e ij When the I is less than or equal to xi, the i row and the j column L of the matrix are equal in distance ij ＝L ji =1, otherwise L ij ＝L ji ＝0；
S43, traversing the matrix L, wherein the matrix L is traversed,
s44, traversing the measurement, wherein the step of measuring,
V re,i (k)＝||v ij ||,if||v ij ||>0(j＝1,...,m,j≠i,k＝k+1)
V min ＝min(V re,i (k))(k≥2)
drag counter C when measuring the speed of i re,i When the speed is more than or equal to 2, speed dragging interference exists and a corresponding measured dragging mark is set to be true;
s45, suppressing the towing interference measurement;
a i ＝‖v i -v‖/Ts
when a is i ＞η a When the measurement i is set to be unreliable, where η a Is an acceleration threshold.
6. The anti-drag-and-fraud method based on dual-band information fusion as defined in claim 5, wherein in the step S5, the distance-speed-angle recognition results of the two bands are fused to accurately recognize the target and the interference, thereby realizing anti-drag-and-fraud; and if the speed difference, the distance difference and the modulus value of the angle difference in the corresponding tracks formed by the two wave bands are smaller than the corresponding threshold, the corresponding track is regarded as a target, and otherwise, the corresponding track is deception jamming.
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